A 36-year geospatial analysis of urbanization dynamics and surface urban heat island effect: Case study of the Bangkok Metropolitan Region

Abstract

This study examines the impact of urbanization on the Surface Urban Heat Island (SUHI) effect in the Bangkok Metropolitan Region (BMR) over a 36-year period, utilizing advanced machine learning techniques to assess changes in land use and land cover (LULC). The research addresses three key questions: (1) How have changes in LULC influenced the dynamics of the urban heat island (UHI) effect in the BMR? (2) What roles do green and blue infrastructure play in mitigating urban heat? (3) How effectively can machine learning models classify LULC changes and provide insights to support sustainable urban planning? The findings reveal a strong correlation between urban growth and increased land surface temperatures (LST), with parks and water bodies exhibiting lower LSTs, emphasizing the importance of green and blue infrastructure in mitigating urban heat. The SUHI effect, initially measured at 3 °C from 1988 to 1991, peaked at 4.8 °C between 2012 and 2019 before slightly declining to 4.1 °C in recent years due to urban greening initiatives. However, ongoing urban development continues to diminish green spaces and water bodies, underscoring the urgent need for sustainable urban planning. Economic factors, including the 1997 Asian Financial Crisis and land tax laws introduced in 2019, influenced land use patterns, further exacerbating the SUHI effect. The research highlights the necessity of integrated urban management and sustainable land use policies to enhance climate resilience in rapidly urbanizing regions like the BMR.